Implementing an iterator vs. looping over a list

I want to loop over a number of rows in a database and I have implemented an object in order to access the rows. Now when using this object I am not sure about the best practice. Implementing an iterator looks nice in the higher-level script but is somewhat unnecessary.

So I wondered, what are the benefits and disadvantages of looping over a list vs. a 'proper' iterator?

Alternatively, would either option make more sense if I changed the structure of my object?

Here is my code using python 2.7:

class process_scope(object):

    __columns = ['id', 'type', 'start', 'end', 'seconds', \
                        'static', 'table_ref']
    def __init__(self, force = False):
        self.force = force
        self._load_timeframes()
        self._reduce_timeframes()

    def __iter__(self):
        return self

    def next(self):
        try:
            return self.timeframes.pop()
        except IndexError:
            raise StopIteration

    def _load_timeframes(self):
        self.timeframes = ((1, 'type_1', 000, 999, 999, 0, 'table_1'),
                           (2, 'type_2', 000, 999, 999, 0, 'table_2'),
                           (3, 'type_3', 000, 999, 999, 1, 'table_3'),
                           (4, 'type_2', 000, 999, 999, 0, 'table_4'),
                           (5, 'type_1', 000, 999, 999, 0, 'table_5'))

    def _reduce_timeframes(self):
        relevant_timeframes = []
        for tf in self.timeframes:
            tf = dict(zip(process_scope.__columns, tf))
            if tf['static'] == 0 or self.force:
                relevant_timeframes.append(tf)

        self.timeframes = relevant_timeframes

Here is the usage option utilizing the iterator...:

for i in process_scope():
    print i

...and the option without implementing the iterator:

iter_ = process_scope().timeframes
for i in iter_:
    print i